improve VS Code docs when using more than one cluster

bcumming · bcumming · commit c4ef1be95df2 · 2025-06-16T15:26:39.000+02:00
diff --git a/docs/access/vscode.md b/docs/access/vscode.md
@@ -27,8 +27,8 @@ This process is also demonstrated in a webinar on [Interactive computing on "Alp
 
 The most flexible method for connecting VSCode is to log in to the Alps system, set up your environment (start a container or uenv, start a session on a compute node), and start the remote server in that environment pre-configured.
 
-!!! note
-    This approach requires that you have a GitHub account, and that the GitHub account is configured with your VS Code editor.
+[](){#ref-vscode-install}
+### Installing the server
 
 The first step is to download the VS Code CLI tool `code`, which CSCS provides for easy download.
 There are two executables, one for using on systems with x86 or ARM CPUs respectively.
@@ -45,16 +45,15 @@ There are two executables, one for using on systems with x86 or ARM CPUs respect
     tar -xf vscode_cli_alpine_x64_cli.tar.gz
     ```
 
-!!! note
-    See the guide on how to manage [architecture-specific binaries][ref-guides-terminal-arch] if you plan to use VScode on both x86 and ARM clusters.
+After downloading, copy the `code` executable to a location in your PATH, so that it is available for future sessions.
 
-Alternatively, download the CLI tool from the [VS Code site](https://code.visualstudio.com/Download) -- take care to select either x86 or Arm64 version that matches the target system.
+Clusters on Alps share a common [home][ref-storage-home] path `HOME=/users/$USER` that is mounted on all clusters.
 
-After downloading, copy the `code` executable to a location in your PATH, so that it is available for future sessions.
+If you want to use VS Code on multiple clusters, possibly with different CPU architectures (Daint, Clariden and Santis use `aarch64` CPUs, and [Eiger][ref-cluster-eiger] uses `x86_64` CPUs), you need to take some additional steps to ensure that VS Code installation and configuration is separated.
 
-??? note "guidance on where to put architecture-specific executables"
-    The home directory can be shared by multiple clusters that might have different micro-architectures, so it is important to separate executables for x86 and aarch64 (ARM) targets.
+First, install the `code` executable in an [architecture-specific path][ref-guides-terminal-arch].
 
+!!! example "Installing VS Code for `x86_64` and `aarch64`"
     In `~/.bashrc`, add the following line (you will need to log in again for this to take effect):
     ```
     export PATH=$HOME/.local/$(uname -m)/bin:$PATH
@@ -66,13 +65,50 @@ After downloading, copy the `code` executable to a location in your PATH, so tha
     mkdir -p $HOME/.local/$(uname -m)/bin
     cp ./code $HOME/.local/$(uname -m)/bin
     ```
+    Repeat this for both `x86_64` and `aarch64` binaries.
+
+By default VS Code will store configuration, data and executables in `$HOME/.vscode-server`.
+To use VS Code on multiple clusters, it is strongly recommended that you create separate `vscode-server` path for each cluster
+by adding the following environment variable definitions to your `~/.bashrc`:
+
+```bash
+export VSCODE_AGENT_FOLDER="$HOME/.vscode-server/$CLUSTER_NAME-tunnel/.vscode-server"
+export VSCODE_CLI_DATA_DIR="$VSCODE_AGENT_FOLDER/cli"
+```
+
+!!! warning
+    You will need to log out and back in after updating `$HOME/.bashrc`, before trying to start the VS Code server for the first time.
+
+[](){#ref-vscode-update}
+### Updating VS Code server
+
+VS Code is continuously being updated, and the version of VS Code on your laptop will most likely be more recent than the version provided by CSCS.
+
+Once you have installed the server, you can easily update it to the latest version:
+
+```console title="Updating VS Code server"
+$ code --version
+code 1.97.2 (commit e54c774e0add60467559eb0d1e229c6452cf8447)
+$ code update
+Successfully updated to 1.101.0 (commit dfaf44141ea9deb3b4096f7cd6d24e00c147a4b1)
+$ code --version
+code 1.101.0 (commit dfaf44141ea9deb3b4096f7cd6d24e00c147a4b1)
+```
+
+It is good practice to periodically update code to keep it in sync with the version on your laptop.
+
+[](){#ref-vscode-starting}
+### Starting and configuring the server
+
+!!! note
+    You need to have a GitHub account to connect a remote tunnel to VS Code.
 
 To set up a remote server on the target system,
-run the `code` executable that you downloaded the `tunnel` argument.
+run the `code` executable that you downloaded with the `tunnel` argument.
 You will be asked to choose whether to log in to Microsoft or GitHub (we have tested with GitHub):
 
-```
-> code tunnel --name=$CLUSTER_NAME-tunnel
+```console
+$ code tunnel --name=$CLUSTER_NAME-tunnel
 ...
 ? How would you like to log in to Visual Studio Code? ›
   Microsoft Account
@@ -85,8 +121,9 @@ You will be asked to choose whether to log in to Microsoft or GitHub (we have te
 You will be requested to go to [github.com/login/device](https://github.com/login/device) and enter an 8-digit code.
 Once you have finished registering the service with GitHub, in VSCode on your PC/laptop open the "remote explorer" pane on the left hand side of the main window, and the connection will be visible under REMOTES (TUNNELS/SSH) -> Tunnels.
 
-!!! note "first time setting up a remote service"
+!!! note "First time setting up a remote service"
     If this is the first time you have followed this procedure, you may have to sign in to GitHub in VSCode.
+
     Click on the Remote Explorer button on the left hand side, and then find the following option:
 
     ```
@@ -99,6 +136,7 @@ Once you have finished registering the service with GitHub, in VSCode on your PC
 
     After signing in and authorizing VSCode, the open tunnel should be visible under REMOTES (TUNNELS/SSH) -> Tunnels.
 
+[](){#ref-vscode-uenv}
 ### Using with uenv
 
 To use a uenv with VSCode, the uenv must be started before calling `code tunnel`.
@@ -124,6 +162,7 @@ Once the tunnel is configured, you can access it from VSCode.
     If you plan to do any intensive work: repeated compilation of large projects or running python code in Jupyter, please see the guide to running on a compute node below.
     Running intensive workloads on login nodes, which are shared resources between all users, is against CSCS [fair usage][ref-policies-fair-use] of Shared Resources policy.
 
+[](){#ref-vscode-compute-nodes}
 ### Running on a compute node
 
 If you plan to do computation using your VSCode, then you should first allocate resources on a compute node and set up your environment there.
@@ -165,13 +204,10 @@ If you plan to do computation using your VSCode, then you should first allocate
     * `-n1` requests a single rank - only one rank/process is required for VSCode
     * `--pty` allows forwarding of terminal I/O, for bash to work interactively
 
+[](){#ref-vscode-containers}
 ### Using with containers
 
-This will use CSCS's **[Container Engine][ref-container-engine]**.
-Using this workflow, one can pull a container from a registry like DockerHub.
-Note that this process also requires that you have a GitHub account, with an authentication and authorization step as described earlier.
-
-This will also use the Remote Tunnel extension and the VS Code connected to the GitHub account (see above).
+This will use CSCS's [Container Engine][ref-container-engine], to launch the container on a compute node and start the VS Code server.
 
 ```toml title="EDF file with image and mount paths"
 image = "nvcr.io#nvidia/pytorch:24.01-py3" # example of PyTorch NGC image
@@ -184,19 +220,24 @@ workdir = "default/working/dir/path"
 
 !!! note
     Ensure that the `code` executable is accessible in the container.
-    It can either be contained in the image, or in one of the mounted folders.
+    It can either be contained in the image, or you can [install][ref-vscode-install] and [update][ref-vscode-update] the server in a path that you [mount][ref-ce-edf-reference-mounts] inside the container in the `mounts` field of the EDF file.
 
-```bash title="Launch container and tunnel"
+Log into the target system, and launch an interactive session with the container image:
+```console
 # launch container on compute node
-srun -N 1 --environment=/absolute/path/to/tomlfile.toml --pty bash
-
-# start tunnel
+$ srun -N 1 --environment=/absolute/path/to/tomlfile.toml --pty bash
+```
 
-cd path/for/code/executable/in/container
-./code tunnel --name=$CLUSTER_NAME-tunnel
+Then on the compute node, you can start the tunnel manually, following the prompts to log in via GitHub:
+```console
+$ cd path/for/code/executable/in/container
+$ ./code tunnel --name=$CLUSTER_NAME-tunnel
 ```
 
 ## Connecting via VSCode UI
 
 !!! warning
-    This approach is not recommended, because while it may be easier to connect via the VS Code UI, it is much more difficult to configure the connection so that you can use uenv, containers or compute nodes.
+    This approach is not recommended, and is not supported by CSCS.
+
+    It is relatively easy to connect to a log in node using the "Connect to Host... (Remote-SSH)" option in the VS Code GUI on your laptop.
+    However, it is complicated and difficult to configure the connection so that the environment used by the VS Code session is in a uenv/container or on a compute node.
diff --git a/docs/software/container-engine/edf.md b/docs/software/container-engine/edf.md
@@ -119,6 +119,7 @@ If false, the container filesystem is read-only.
     writable = true
     ```
 
+[](){#ref-ce-edf-reference-mounts}
 ### `mounts`
 
  |             |       |
